Efficient RkNN Retrieval with Arbitrary Non-Metric Similarity Measures

Summary: RkNN under arbitrary non-metric dissimilarities, where query-time aggregation over attribute distances defines the distance. Uses AL-Tree for group-level reasoning to prune RkNN, beating naive scans and block-based methods on real and synthetic data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 10059
Venue: VLDB
Year: 2010
Pagerank: 4.1945683e-05
Overall Rank: 12,268 | 14.66%
DOI: -

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Authors

1. Deepak P
2. Prasad M Deshpande

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 8 of 8 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
2	R-Trees: A Dynamic Index Structure For Spatial Searching	1984	SIGMOD	0.0032169493
7	Optimal Aggregation Algorithms for Middleware [Extended Abstract]	2001	PODS	0.0015496097
91	M-tree: An Efficient Access Method for Similarity Search in Metric Spaces	1997	VLDB	0.0005181666
601	Influence Sets Based on Reverse Nearest Neighbor Queries	2000	SIGMOD	0.00019375875
1,933	Reverse kNN Search in Arbitrary Dimensionality	2004	VLDB	0.00010038508
2,009	IO-Top-k: Index-access Optimized Top-k Query Processing	2006	VLDB	9.7977564e-05
2,454	Efficient Computation of Reverse Skyline Queries	2007	VLDB	8.778281e-05
4,070	Efficient Reverse k-Nearest Neighbor Search in Arbitrary Metric Spaces	2006	SIGMOD	6.4784181e-05

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